A must have text for risk modelling and portfolio optimization using R.

This book introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. This edition has been extensively revised to include new topics on risk surfaces and probabilistic utility optimization as well as an extended introduction to R language.Financial Risk Modelling and Portfolio Optimization with R:

Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field.

Is accompanied by a supporting website featuring examples and case studies in R.

Includes updated list of R packages for enabling the reader to replicate the results in the book.

Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer–lab classes and is therefore suitable for self–study.

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Primary Market: Practitioners in finance and portfolio optimisation who are well versed in risk management and using R Secondary Market: Graduate and postgraduate students in finance, economics, risk management

Textul de pe ultima copertă

A must have text for risk modelling and portfolio optimization using R.

This book introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. This edition has been extensively revised to include new topics on risk surfaces and probabilistic utility optimization as well as an extended introduction to R language.Financial Risk Modelling and Portfolio Optimization with R:

Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field.

Is accompanied by a supporting website featuring examples and case studies in R.

Includes updated list of R packages for enabling the reader to replicate the results in the book.

Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer–lab classes and is therefore suitable for self–study.